Visible to the public Biblio

Found 203 results

Filters: First Letter Of Last Name is V  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U [V] W X Y Z   [Show ALL]
Vimalkumar, K., Radhika, N..  2017.  A Big Data Framework for Intrusion Detection in Smart Grids Using Apache Spark. 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI). :198–204.

Technological advancement enables the need of internet everywhere. The power industry is not an exception in the technological advancement which makes everything smarter. Smart grid is the advanced version of the traditional grid, which makes the system more efficient and self-healing. Synchrophasor is a device used in smart grids to measure the values of electric waves, voltages and current. The phasor measurement unit produces immense volume of current and voltage data that is used to monitor and control the performance of the grid. These data are huge in size and vulnerable to attacks. Intrusion Detection is a common technique for finding the intrusions in the system. In this paper, a big data framework is designed using various machine learning techniques, and intrusions are detected based on the classifications applied on the synchrophasor dataset. In this approach various machine learning techniques like deep neural networks, support vector machines, random forest, decision trees and naive bayes classifications are done for the synchrophasor dataset and the results are compared using metrics of accuracy, recall, false rate, specificity, and prediction time. Feature selection and dimensionality reduction algorithms are used to reduce the prediction time taken by the proposed approach. This paper uses apache spark as a platform which is suitable for the implementation of Intrusion Detection system in smart grids using big data analytics.

Vimercati, S. de Capitani di, Foresti, S., Paraboschi, S., Samarati, P..  2020.  Enforcing Corporate Governance's Internal Controls and Audit in the Cloud. 2020 IEEE 13th International Conference on Cloud Computing (CLOUD). :453–461.
More and more organizations are today using the cloud for their business as a quite convenient alternative to in-house solutions for storing, processing, and managing data. Cloud-based solutions are then permeating almost all aspects of business organizations, resulting appealing also for functions that, already in-house, may result sensitive or security critical, and whose enforcement in the cloud requires then particular care. In this paper, we provide an approach for securely relying on cloud-based services for the enforcement of Internal Controls and Audit (ICA) functions for corporate governance. Our approach is based on the use of selective encryption and of tags to provide a level of self-protection to data and for enabling only authorized parties to access data and perform operations on them, providing privacy and integrity guarantees, as well as accountability and non-repudiation.
Vincur, J., Navrat, P., Polasek, I..  2017.  VR City: Software Analysis in Virtual Reality Environment. 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C). :509–516.
This paper presents software visualization tool that utilizes the modified city metaphor to represent software system and related analysis data in virtual reality environment. To better address all three kinds of software aspects we propose a new layouting algorithm that provides a higher level of detail and position the buildings according to the coupling between classes that they represent. Resulting layout allows us to visualize software metrics and source code modifications at the granularity of methods, visualize method invocations involved in program execution and to support the remodularization analysis. To further reduce the cognitive load and increase efficiency of 3D visualization we allow users to observe and interact with our city in immersive virtual reality environment that also provides a source code browsing feature. We demonstrate the use of our approach on two open-source systems.
Visala, K., Keating, A., Khan, R.H..  2014.  Models and tools for the high-level simulation of a name-based interdomain routing architecture. Computer Communications Workshops (INFOCOM WKSHPS), 2014 IEEE Conference on. :55-60.

The deployment and operation of global network architectures can exhibit complex, dynamic behavior and the comprehensive validation of their properties, without actually building and running the systems, can only be achieved with the help of simulations. Packet-level models are not feasible in the Internet scale, but we are still interested in the phenomena that emerge when the systems are run in their intended environment. We argue for the high-level simulation methodology and introduce a simulation environment based on aggregate models built on state-of-the-art datasets available while respecting invariants observed in measurements. The models developed are aimed at studying a clean slate name-based interdomain routing architecture and provide an abundance of parameters for sensitivity analysis and a modular design with a balanced level of detail in different aspects of the model. In addition to introducing several reusable models for traffic, topology, and deployment, we report our experiences in using the high-level simulation approach and potential pitfalls related to it.

Visalli, Nicholas, Deng, Lin, Al-Suwaida, Amro, Brown, Zachary, Joshi, Manish, Wei, Bingyang.  2019.  Towards Automated Security Vulnerability and Software Defect Localization. 2019 IEEE 17th International Conference on Software Engineering Research, Management and Applications (SERA). :90–93.

Security vulnerabilities and software defects are prevalent in software systems, threatening every aspect of cyberspace. The complexity of modern software makes it hard to secure systems. Security vulnerabilities and software defects become a major target of cyberattacks which can lead to significant consequences. Manual identification of vulnerabilities and defects in software systems is very time-consuming and tedious. Many tools have been designed to help analyze software systems and to discover vulnerabilities and defects. However, these tools tend to miss various types of bugs. The bugs that are not caught by these tools usually include vulnerabilities and defects that are too complicated to find or do not fall inside of an existing rule-set for identification. It was hypothesized that these undiscovered vulnerabilities and defects do not occur randomly, rather, they share certain common characteristics. A methodology was proposed to detect the probability of a bug existing in a code structure. We used a comprehensive experimental evaluation to assess the methodology and report our findings.

Vishagini, V., Rajan, A. K..  2018.  An Improved Spam Detection Method with Weighted Support Vector Machine. 2018 International Conference on Data Science and Engineering (ICDSE). :1–5.
Email is the most admired method of exchanging messages using the Internet. One of the intimidations to email users is to detect the spam they receive. This can be addressed using different detection and filtering techniques. Machine learning algorithms, especially Support Vector Machine (SVM), can play vital role in spam detection. We propose the use of weighted SVM for spam filtering using weight variables obtained by KFCM algorithm. The weight variables reflect the importance of different classes. The misclassification of emails is reduced by the growth of weight value. We evaluate the impact of spam detection using SVM, WSVM with KPCM and WSVM with KFCM.UCI Repository SMS Spam base dataset is used for our experimentation.
Vishwakarma, L., Das, D..  2020.  BSS: Blockchain Enabled Security System for Internet of Things Applications. 2020 IEEE 19th International Symposium on Network Computing and Applications (NCA). :1—4.

In the Internet of Things (IoT), devices can interconnect and communicate autonomously, which requires devices to authenticate each other to exchange meaningful information. Otherwise, these things become vulnerable to various attacks. The conventional security protocols are not suitable for IoT applications due to the high computation and storage demand. Therefore, we proposed a blockchain-enabled secure storage and communication scheme for IoT applications, called BSS. The scheme ensures identification, authentication, and data integrity. Our scheme uses the security advantages of blockchain and helps to create safe zones (trust batch) where authenticated objects interconnect securely and do communication. A secure and robust trust mechanism is employed to build these batches, where each device has to authenticate itself before joining the trust batch. The obtained results satisfy the IoT security requirements with 60% reduced computation, storage and communication cost compared with state-of-the-art schemes. BSS also withstands various cyberattacks such as impersonation, message replay, man-in-the-middle, and botnet attacks.

Vishwakarma, Ruchi, Jain, Ankit Kumar.  2019.  A Honeypot with Machine Learning based Detection Framework for defending IoT based Botnet DDoS Attacks. 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI). :1019–1024.

With the tremendous growth of IoT botnet DDoS attacks in recent years, IoT security has now become one of the most concerned topics in the field of network security. A lot of security approaches have been proposed in the area, but they still lack in terms of dealing with newer emerging variants of IoT malware, known as Zero-Day Attacks. In this paper, we present a honeypot-based approach which uses machine learning techniques for malware detection. The IoT honeypot generated data is used as a dataset for the effective and dynamic training of a machine learning model. The approach can be taken as a productive outset towards combatting Zero-Day DDoS Attacks which now has emerged as an open challenge in defending IoT against DDoS Attacks.

Visoottiviseth, Vasaka, Phungphat, Atit, Puttawong, Nuntapob, Chantaraumporn, Pamanut, Haga, Jason.  2018.  Lord of Secure: The Virtual Reality Game for Educating Network Security. 2018 Seventh ICT International Student Project Conference (ICT-ISPC). :1-6.

 At the present, the security on the Internet is very sensitive and important. Most of the computer science curricula in universities and institutes of higher education provides this knowledge in term of computer and network security. Therefore, students studying in the information technology area need to have some basic knowledge about the security in order to prevent the potential attacks and protect themselves from hackers or intruders. Unfortunately, the network security concept is moderately abstract when students learn in the traditional lecture-based class. In this paper, to motivate and help students to perceive better than in the traditional classroom, we propose a security game called “Lord of Secure”, which is a virtual reality (VR) game on Android for education. It is an alternative learning materials for learners to gain the knowledge about the network security effectively. The game composes of main topics of the network security such as Firewall, IDS, IPS, and Honey pot. Moreover, the game will give the players knowledge about network security through the virtual world. The game also contains several quizzes including pretest and posttest, so players will know how much they gain more knowledge about network security by comparing scores before and after playing the game.

Viswanathan, Balaji, Goel, Seep, Verma, Mudit, Kothari, Ravi.  2016.  Evidential Reasoning Based Fault Diagnosis. Proceedings of the Posters and Demos Session of the 17th International Middleware Conference. :17–18.

Fault diagnosis in IT environments is complicated because (i) most monitors have shared specificity (high amount of memory utilization can result from a large number of causes), (ii) it is hard to deploy and maintain enough sensors to ensure adequate coverage, and (iii) some functionality may be provided as-a-service by external parties with limited visibility and simultaneous availability of alert data. To systematically incorporate uncertainty and to be able to fuse information from multiple sources, we propose the use of Dempster-Shafer Theory (DST) of evidential reasoning for fault diagnosis and show its efficacy in the context of a distributed application.

Viticchié, Alessio, Basile, Cataldo, Avancini, Andrea, Ceccato, Mariano, Abrath, Bert, Coppens, Bart.  2016.  Reactive Attestation: Automatic Detection and Reaction to Software Tampering Attacks. Proceedings of the 2016 ACM Workshop on Software PROtection. :73–84.

Anti-tampering is a form of software protection conceived to detect and avoid the execution of tampered programs. Tamper detection assesses programs' integrity with load or execution-time checks. Avoidance reacts to tampered programs by stopping or rendering them unusable. General purpose reactions (such as halting the execution) stand out like a lighthouse in the code and are quite easy to defeat by an attacker. More sophisticated reactions, which degrade the user experience or the quality of service, are less easy to locate and remove but are too tangled with the program's business logic, and are thus difficult to automate by a general purpose protection tool. In the present paper, we propose a novel approach to anti-tampering that (i) fully automatically applies to a target program, (ii) uses Remote Attestation for detection purposes and (iii) adopts a server-side reaction that is difficult to block by an attacker. By means of Client/Server Code Splitting, a crucial part of the program is removed from the client and executed on a remote trusted server in sync with the client. If a client program provides evidences of its integrity, the part moved to the server is executed. Otherwise, a server-side reaction logic may (temporarily or definitely) decide to stop serving it. Therefore, a tampered client application can not continue its execution. We assessed our automatic protection tool on a case study Android application. Experimental results show that all the original and tampered executions are correctly detected, reactions are promptly applied, and execution overhead is on an acceptable level.

Vizarreta, P., Heegaard, P., Helvik, B., Kellerer, W., Machuca, C. M..  2017.  Characterization of failure dynamics in SDN controllers. 2017 9th International Workshop on Resilient Networks Design and Modeling (RNDM). :1–7.

With Software Defined Networking (SDN) the control plane logic of forwarding devices, switches and routers, is extracted and moved to an entity called SDN controller, which acts as a broker between the network applications and physical network infrastructure. Failures of the SDN controller inhibit the network ability to respond to new application requests and react to events coming from the physical network. Despite of the huge impact that a controller has on the network performance as a whole, a comprehensive study on its failure dynamics is still missing in the state of the art literature. The goal of this paper is to analyse, model and evaluate the impact that different controller failure modes have on its availability. A model in the formalism of Stochastic Activity Networks (SAN) is proposed and applied to a case study of a hypothetical controller based on commercial controller implementations. In case study we show how the proposed model can be used to estimate the controller steady state availability, quantify the impact of different failure modes on controller outages, as well as the effects of software ageing, and impact of software reliability growth on the transient behaviour.

Vizarreta, Petra, Sakic, Ermin, Kellerer, Wolfgang, Machuca, Carmen Mas.  2019.  Mining Software Repositories for Predictive Modelling of Defects in SDN Controller. 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). :80-88.

In Software Defined Networking (SDN) control plane of forwarding devices is concentrated in the SDN controller, which assumes the role of a network operating system. Big share of today's commercial SDN controllers are based on OpenDaylight, an open source SDN controller platform, whose bug repository is publicly available. In this article we provide a first insight into 8k+ bugs reported in the period over five years between March 2013 and September 2018. We first present the functional components in OpenDaylight architecture, localize the most vulnerable modules and measure their contribution to the total bug content. We provide high fidelity models that can accurately reproduce the stochastic behaviour of bug manifestation and bug removal rates, and discuss how these can be used to optimize the planning of the test effort, and to improve the software release management. Finally, we study the correlation between the code internals, derived from the Git version control system, and software defect metrics, derived from Jira issue tracker. To the best of our knowledge, this is the first study to provide a comprehensive analysis of bug characteristics in a production grade SDN controller.

Vizer, L. M., Sears, A..  2015.  Classifying Text-Based Computer Interactions for Health Monitoring. IEEE Pervasive Computing. 14:64–71.

Detecting early trends indicating cognitive decline can allow older adults to better manage their health, but current assessments present barriers precluding the use of such continuous monitoring by consumers. To explore the effects of cognitive status on computer interaction patterns, the authors collected typed text samples from older adults with and without pre-mild cognitive impairment (PreMCI) and constructed statistical models from keystroke and linguistic features for differentiating between the two groups. Using both feature sets, they obtained a 77.1 percent correct classification rate with 70.6 percent sensitivity, 83.3 percent specificity, and a 0.808 area under curve (AUC). These results are in line with current assessments for MC–a more advanced disease–but using an unobtrusive method. This research contributes a combination of features for text and keystroke analysis and enhances understanding of how clinicians or older adults themselves might monitor for PreMCI through patterns in typed text. It has implications for embedded systems that can enable healthcare providers and consumers to proactively and continuously monitor changes in cognitive function.

Vlachokostas, Alex, Prousalidis, John, Spathis, Dimosthenis, Nikitas, Mike, Kourmpelis, Theo, Dallas, Stefanos, Soghomonian, Zareh, Georgiou, Vassilis.  2019.  Ship-to-Grid Integration: Environmental Mitigation and Critical Infrastructure Resilience. 2019 IEEE Electric Ship Technologies Symposium (ESTS). :542–547.

The United States and European Union have an increasing number of projects that are engaging end-use devices for improved grid capabilities. Areas such as building-to-grid and vehicle-to-grid are simple examples of these advanced capabilities. In this paper, we present an innovative concept study for a ship-to-grid integration. The goal of this study is to simulate a two-way power flow between ship(s) and the grid with GridLAB-D for the port of Kyllini in Greece, where a ship-to-shore interconnection was recently implemented. Extending this further, we explore: (a) the ability of ships to meet their load demand needs, while at berth, by being supplied with energy from the electric grid and thus powering off their diesel engines; and (b) the ability of ships to provide power to critical loads onshore. As a result, the ship-to-grid integration helps (a) mitigate environmental pollutants from the ships' diesel engines and (b) provide resilience to nearby communities during a power disruption due to natural disasters or man-made threats.

Vlachos, Vasileios, Stamatiou, Yannis C., Madhja, Adelina, Nikoletseas, Sotiris.  2017.  Privacy Flag: A Crowdsourcing Platform for Reporting and Managing Privacy and Security Risks. Proceedings of the 21st Pan-Hellenic Conference on Informatics. :27:1–27:4.

Nowadays we are witnessing an unprecedented evolution in how we gather and process information. Technological advances in mobile devices as well as ubiquitous wireless connectivity have brought about new information processing paradigms and opportunities for virtually all kinds of scientific and business activity. These new paradigms rest on three pillars: i) numerous powerful portable devices operated by human intelligence, ubiquitous in space and available, most of the time, ii) unlimited environment sensing capabilities of the devices, and iii) fast networks connecting the devices to Internet information processing platforms and services. These pillars implement the concepts of crowdsourcing and collective intelligence. These concepts describe online services that are based on the massive participation of users and the capabilities of their order to produce results and information which are "more than the sum of the part". The EU project Privacy Flag relies exactly on these two concepts in order to mobilize roaming citizens to contribute, through crowdsourcing, information about risky applications and dangerous web sites whose processing may produce emergent threat patterns, not evident in the contributed information alone, reelecting a collective intelligence action. Crowdsourcing and collective intelligence, in this context, has numerous advantages, such as raising privacy-awareness among people. In this paper we summarize our work in this project and describe the capabilities and functionalities of the Privacy Flag Platform.

Vladimirovich, Menshikh Valerii, Iurevich, Kalkov Dmitrii, Evgenevna, Spiridonova Natalia.  2019.  Model of optimization of arrangement of video surveillance means with regard to ensuring their own security. 2019 1st International Conference on Control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA). :4–7.
Currently, video surveillance systems play an important role in ensuring the safety of citizens, their property, etc., which greatly contributes to the reduction of crime. Due to the high intrinsic value and/or high efficiency of their use for the prevention and detection of crimes, they themselves often become the objects of illegal actions (theft, damage). The main purpose of video surveillance systems is to provide continuous visual monitoring of the situation at a particular facility or territory, as well as event registration. The breakdown of the camera is detected by the loss of signal in the control center. However, the absence of a signal for reasons other than these can also be caused by an accident on the power line, a communication channel break, software or hardware breakdown of the camera itself. In this regard, there is a problem of determining the exact cause of the lack of signal and, consequently, the need for a rapid response to it. The paper proposes an approach of video surveillance arrangement according to their main functional purpose, as well as their ability to monitor each other. Based on this approach, a mathematical model of the choice of locations and conditions of location of video surveillance equipment from a set of potentially acceptable as a problem of nonlinear Boolean programming is developed. This model maximizes the functionality of the video surveillance system, taking into account the importance of areas and objects of surveillance with restrictions on the number of video surveillance of each type, the nature of the terrain and existing buildings. An algorithm for solving this problem is proposed.
Vliegen, Jo, Rabbani, Md Masoom, Conti, Mauro, Mentens, Nele.  2019.  SACHa: Self-Attestation of Configurable Hardware. 2019 Design, Automation Test in Europe Conference Exhibition (DATE). :746–751.
Device attestation is a procedure to verify whether an embedded device is running the intended application code. This way, protection against both physical attacks and remote attacks on the embedded software is aimed for. With the wide adoption of Field-Programmable Gate Arrays or FPGAs, hardware also became configurable, and hence susceptible to attacks (just like software). In addition, an upcoming trend for hardware-based attestation is the use of configurable FPGA hardware. Therefore, in order to attest a whole system that makes use of FPGAs, the status of both the software and the hardware needs to be verified, without the availability of a tamper-resistant hardware module.In this paper, we propose a solution in which a prover core on the FPGA performs an attestation of the entire FPGA, including a self-attestation. This way, the FPGA can be used as a tamper-resistant hardware module to perform hardware-based attestation of a processor, resulting in a protection of the entire hardware/software system against malicious code updates.
Vo, Tri Hoang, Fuhrmann, Woldemar, Fischer-Hellmann, Klaus-Peter, Furnell, Steven.  2019.  Efficient Privacy-Preserving User Identity with Purpose-Based Encryption. 2019 International Symposium on Networks, Computers and Communications (ISNCC). :1–8.
In recent years, users may store their Personal Identifiable Information (PII) in the Cloud environment so that Cloud services may access and use it on demand. When users do not store personal data in their local machines, but in the Cloud, they may be interested in questions such as where their data are, who access it except themselves. Even if Cloud services specify privacy policies, we cannot guarantee that they will follow their policies and will not transfer user data to another party. In the past 10 years, many efforts have been taken in protecting PII. They target certain issues but still have limitations. For instance, users require interacting with the services over the frontend, they do not protect identity propagation between intermediaries and against an untrusted host, or they require Cloud services to accept a new protocol. In this paper, we propose a broader approach that covers all the above issues. We prove that our solution is efficient: the implementation can be easily adapted to existing Identity Management systems and the performance is fast. Most importantly, our approach is compliant with the General Data Protection Regulation from the European Union.
Voas, Jeffrey.  2016.  Building Blocks of the Internet of Things. :1–2.

Five core primitives belonging to most distributed systems are presented. These primitives apply well to systems with large amounts of data, scalability concerns, heterogeneity concerns, temporal concerns, and elements of unknown pedigree with possible nefarious intent. These primitives form the basic building blocks for a Network of 'Things' (NoT), including the Internet of Things (IoT). This talk discusses the underlying and foundational science of IoT. To our knowledge, the ideas and the manner in which the science underlying IoT is presented here is unique.

Voas, Jeffrey.  2016.  Building Blocks of the Internet of Things. :1–2.

Five core primitives belonging to most distributed systems are presented. These primitives apply well to systems with large amounts of data, scalability concerns, heterogeneity concerns, temporal concerns, and elements of unknown pedigree with possible nefarious intent. These primitives form the basic building blocks for a Network of 'Things' (NoT), including the Internet of Things (IoT). This talk discusses the underlying and foundational science of IoT. To our knowledge, the ideas and the manner in which the science underlying IoT is presented here is unique.

Vöelp, Marcus, Esteves-Verissimo, Paulo.  2018.  Intrusion-Tolerant Autonomous Driving. 2018 IEEE 21st International Symposium on Real-Time Distributed Computing (ISORC). :130–133.
Fully autonomous driving is one if not the killer application for the upcoming decade of real-time systems. However, in the presence of increasingly sophisticated attacks by highly skilled and well equipped adversarial teams, autonomous driving must not only guarantee timeliness and hence safety. It must also consider the dependability of the software concerning these properties while the system is facing attacks. For distributed systems, fault-and-intrusion tolerance toolboxes already offer a few solutions to tolerate partial compromise of the system behind a majority of healthy components operating in consensus. In this paper, we present a concept of an intrusion-tolerant architecture for autonomous driving. In such a scenario, predictability and recovery challenges arise from the inclusion of increasingly more complex software on increasingly less predictable hardware. We highlight how an intrusion tolerant design can help solve these issues by allowing timeliness to emerge from a majority of complex components being fast enough, often enough while preserving safety under attack through pre-computed fail safes.
Voigt, S., Schoepfer, E., Fourie, C., Mager, A..  2014.  Towards semi-automated satellite mapping for humanitarian situational awareness. Global Humanitarian Technology Conference (GHTC), 2014 IEEE. :412-416.

Very high resolution satellite imagery used to be a rare commodity, with infrequent satellite pass-over times over a specific area-of-interest obviating many useful applications. Today, more and more such satellite systems are available, with visual analysis and interpretation of imagery still important to derive relevant features and changes from satellite data. In order to allow efficient, robust and routine image analysis for humanitarian purposes, semi-automated feature extraction is of increasing importance for operational emergency mapping tasks. In the frame of the European Earth Observation program COPERNICUS and related research activities under the European Union's Seventh Framework Program, substantial scientific developments and mapping services are dedicated to satellite based humanitarian mapping and monitoring. In this paper, recent results in methodological research and development of routine services in satellite mapping for humanitarian situational awareness are reviewed and discussed. Ethical aspects of sensitivity and security of humanitarian mapping are deliberated. Furthermore methods for monitoring and analysis of refugee/internally displaced persons camps in humanitarian settings are assessed. Advantages and limitations of object-based image analysis, sample supervised segmentation and feature extraction are presented and discussed.

Voitovych, O., Kupershtein, L., Pavlenko, I..  2017.  Hidden Process Detection for Windows Operating Systems. 2017 4th International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S T). :460–464.

Rootkits detecting in the Windows operating system is an important part of information security monitoring and audit system. Methods of hided process detection were analyzed. The software is developed which implements the four methods of hidden process detection in a user mode (PID based method, the descriptor based method, system call based method, opened windows based method) to use in the monitoring and audit systems.

Völker, Benjamin, Scholls, Philipp M., Schubert, Tobias, Becker, Bernd.  2018.  Towards the Fusion of Intrusive and Non-Intrusive Load Monitoring: A Hybrid Approach. Proceedings of the Ninth International Conference on Future Energy Systems. :436-438.

With Electricity as a fundamental part of our life, its production has still large, negative environmental impact. Therefore, one strain of research is to optimize electricity usage by avoiding its unnecessary consumption or time its consumption when green energy is available. The shift towards an Advanced Metering Infrastructure (AMI) allows to optimize energy distribution based on the current load at residence level. However, applications such as Demand Management and Advanced Load Forecasting require information further down at device level, which cannot be provided by standard electricity meters nor existing AMIs. Hence, different approaches for appliance monitoring emerged over the past 30 years which are categorized into Intrusive systems requiring multiple distributed sensors and Non-Intrusive systems requiring a single unobtrusive sensor. Although each category has been individually explored, hybrid approaches have received little attention. Our experiments highlight that variable consumer devices (e.g. PCs) are detrimental to the detection performance of non-intrusive systems. We further show that their influence can be inhibited by using sensor data from additional intrusive sensors. Even fairly straightforward sensor fusion techniques lead to a classification performance (F1) gain from 84.88 % to 93.41 % in our test setup. As this highlights the potential to contribute to the global goal of saving energy, we define further research directions for hybrid load monitoring systems.